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Cost-Aware Abstention for LLM-Based IT Ticket Classification

Paper recorded by Signals 4 on 2026-10-22 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-22 on arXiv · recorded by Signals 4 on 2026-10-23

Category: cs.AI · 人工智能 · first seen 2026-10-23

Abstract

Wrong automatic routing of an IT support ticket can cost more than human triage. We evaluate cost-aware abstention as an offline, cost-conditional readiness assessment: select a routing policy on calibration data under explicit costs, then evaluate that frozen policy once on held-out test data. On a public 47,837-ticket, eight-class corpus, we compare four trained non-LLM classifiers with four lar

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#182 most recent of 960 cs.AI papers we have recorded · ↑ newer: Direct Pass@$k$ Optimization for Thought Pruning: Balancing Quality an · ↓ older: METTA: Memory-Enhanced Test-Time Adaptation for Meta-Reinforcement Lea
Cite this page: Cost-Aware Abstention for LLM-Based IT Ticket Classification: the #182 most recent of 960 cs.AI papers we have recorded (as of 2026-10-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/cost-aware-abstention-for-llm-based-it-ticket-classification.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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